The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
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Timeline
X Demographics
Mendeley readers
Title |
Development and Validation of Manually Modified and Supervised Machine Learning Clinical Assessment Algorithms for Malaria in Nigerian Children
|
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Published in |
Frontiers in Artificial Intelligence, February 2022
|
DOI | 10.3389/frai.2021.554017 |
Pubmed ID | |
Authors |
Megan McLaughlin, Karell G. Pellé, Samuel V. Scarpino, Aisha Giwa, Ezra Mount-Finette, Nada Haidar, Fatima Adamu, Nirmal Ravi, Adam Thompson, Barry Heath, Sabine Dittrich, Barry Finette |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 17% |
Switzerland | 1 | 8% |
India | 1 | 8% |
Unknown | 8 | 67% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 9 | 75% |
Scientists | 2 | 17% |
Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 32 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Unspecified | 9 | 28% |
Student > Ph. D. Student | 3 | 9% |
Professor | 1 | 3% |
Student > Postgraduate | 1 | 3% |
Other | 1 | 3% |
Other | 0 | 0% |
Unknown | 17 | 53% |
Readers by discipline | Count | As % |
---|---|---|
Unspecified | 9 | 28% |
Medicine and Dentistry | 3 | 9% |
Social Sciences | 1 | 3% |
Business, Management and Accounting | 1 | 3% |
Unknown | 18 | 56% |